This article presents a wearable system that localizes people in the indoor environment, using data from inertial sensors. The sensors measure the parameters of human motion, tracking the movements of the torso and foot. For this purpose, they were integrated with shirt and the shoe insole. The values of acceleration measured by the sensors are sent via Bluetooth to a smartphone. The localization algorithm implemented on the smartphone, presented here, merges data from the shirt and the shoe to track the steps made by the user and filter out the localization errors caused by movements the shirt and torso. The experimental verification of the algorithm is also presented.

The removal of inclusions is a major challenge prior to the casting process, as they cause a discontinuity in the cast material, thereby lowering its mechanical properties and have a negative impact on the feeding capability and fluidity of the liquid alloys. In order to achieve adequate melt quality for casting, it is important to clean the melts from inclusions, for which there are numerous methods that can be used. In the course of the presented research, the inclusion removal efficiency of rotary degassing coupled with the addition of different fluxes was investigated. The effects of various cleaning fluxes on the inclusion content and the susceptibility to pore formation were compared by the investigation of K-mold samples and the evaluation of Density Index values at different stages of melt preparation. The chemical composition of the applied fluxes was characterized by X-ray powder diffraction, while the melting temperature of the fluxes was evaluated by derivatographic measurements. It was found that only the solute hydrogen content of the liquid metal could be significantly reduced during the melt treatments, however, better inclusion removal efficiency could be achieved with fluxes that have a low melting temperature.